English

Systemic robustness: a mean-field particle system approach

Probability 2023-08-30 v2 Mathematical Finance

Abstract

This paper is concerned with the problem of budget control in a large particle system modeled by stochastic differential equations involving hitting times, which arises from considerations of systemic risk in a regional financial network. Motivated by Tang and Tsai (Ann. Probab., 46(2018), pp. 1597{1650), we focus on the number or proportion of surviving entities that never default to measure the systemic robustness. First we show that both the mean-field particle system and its limiting McKean-Vlasov equation are well-posed by virtue of the notion of minimal solutions. We then establish a connection between the proportion of surviving entities in the large particle system and the probability of default in the limiting McKean-Vlasov equation as the size of the interacting particle system N tends to infinity. Finally, we study the asymptotic efficiency of budget control in different economy regimes: the expected number of surviving entities is of constant order in a negative economy; it is of order of the square root of N in a neutral economy; and it is of order N in a positive economy where the budget's effect is negligible.

Keywords

Cite

@article{arxiv.2212.08518,
  title  = {Systemic robustness: a mean-field particle system approach},
  author = {Erhan Bayraktar and Gaoyue Guo and Wenpin Tang and Yuming Paul Zhang},
  journal= {arXiv preprint arXiv:2212.08518},
  year   = {2023}
}

Comments

33 pages

R2 v1 2026-06-28T07:39:05.966Z